Most racing-based computer games provide a mode for competing against computer-controlled opponents that use a simple form of artificial intelligence (AI) to negotiate the race track or course in a simulated “human-like” fashion. However, despite the “human-like” goal of such AI, the result tends to appear quite non-human upon close observation. For example, the computer opponent may travel along an ideal or prescribed racing line on the course, whereas a human competitor inadvertently introduces continuous imperfections into his or her driving, such as over/under turning, over/under accelerating, over/under braking, and early/late reactions. However, it is just such imperfections that characterize a “human-like” competitor.
A typical AI motion control system effectively provides a computer opponent with a reaction time of 1/60th of a second in the USA or 1/50th of a second in Europe (i.e., for each frame repaint interval in the virtual reality environment). Therefore, computer control of the AI opponent in reaction to any “visual” (e.g., distance to a corner) and “physical” (e.g., loss of traction) stimuli from the virtual reality environment occurs 50 or 60 times a second. No human player can react so quickly, so frequently, or so ideally as to compete with such a perfect computer controlled opponent.
Therefore, one specific source of the non-human-like behavior of computer opponents is that the typical AI motion control system follows this prescribed racing line too perfectly, correcting its off-line motion at super-human speed (e.g., 60 times a second) and barely deviating from this ideal path. A virtual observer could follow a typical AI controlled vehicle around a course and find little or no deviation in the vehicle's path from the ideal path and little or no deviation in the AI controlled vehicle's path from lap to lap.